Online modelling based on Genetic Programming

Stephan Winkler, Hajrudin Efendic, Michael Affenzeller, Luigi Del Re, Stefan Wagner

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


Genetic Programming (GP), a heuristic optimisation technique based on the theory of Genetic Algorithms (GAs), is a method successfully used to identify non-linear model structures by analysing a system’s measured signals. Mostly, it is used as an offline tool that means that structural analysis is done after collecting all available identification data. In this paper, we propose an enhanced on-line GP approach that is able to adapt its behaviour to new observations while the GP process is executed. Furthermore, an approach using GP for online Fault Diagnosis (FD) is described, and finally test results using measurement data of NOx emissions of a BMW diesel engine are discussed.

Original languageEnglish
Pages (from-to)255-270
Number of pages16
JournalInternational Journal of Intelligent Systems Technologies and Applications
Issue number2-3
Publication statusPublished - 2007


  • data driven model identification
  • fault diagnosis
  • FD
  • genetic programming
  • GP
  • machine learning
  • online modelling
  • self-adaption


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